Sally Ward-Foxton

Sally Ward-Foxton covers AI technology and semiconductor hardware for EE Times, with a focus on AI accelerators, edge processors, and the chips and companies that support advanced machine-learning workloads. Her reporting stands out for its close attention to how specific silicon architectures, software stacks, and business models interact, rather than treating AI as a generic trend. She has spent more than 18 years writing about the electronics industry and now concentrates on AI-centric semiconductors and the European chip industry.

AI Accelerators and Semiconductor Startups

Ward-Foxton reports mainly on AI accelerators and the devices designed to run large neural-network workloads efficiently. Her coverage includes stories on cost-efficient AI at scale that frame hardware choices alongside software strategies, such as an article arguing that achieving AI at scale is as much a software issue as it is a chip-design problem.

She follows emerging companies in the accelerator space, covering startups like ChipAgents and its agentic chip-design platform in the context of funding rounds and early customer traction.

She also tracks novel AI silicon, writing about Applied Brain Research’s first state-space network chip for real-time speech AI at ultra-low power, highlighting both the architecture and its target applications. In work such as “Cerebras IPO Revives AI Chip Startup Fever,” she links technical innovation to capital markets and industry cycles, showing how new architectures and public listings influence the broader AI chip startup landscape.

Neuromorphic Computing and Edge AI Vision

A significant part of Ward-Foxton’s portfolio is dedicated to neuromorphic computing and sensing, where she treats the field as a concrete set of hardware and application choices rather than an abstract research topic. In an EE Times special project on neuromorphic technology, she examines how event-based cameras and spiking neural networks could reshape computer vision and automotive systems, including pieces on “Cars That Think Like You” and upcoming shifts in computer vision driven by neuromorphic sensing.

Her work on neuromorphic sensors for consumer electronics includes interviews with industry figures such as Prophesee CEO Luca Verre, exploring how retina-inspired sensors move from lab to product and what commercial trajectories look like. She also profiles companies like Opteran, which reverse-engineer insect brains to develop navigation and movement algorithms, using these examples to show how biologically inspired approaches translate into robotics and edge AI systems.

Across these articles, she connects unconventional architectures and sensors to mainstream use cases, emphasising practical deployment paths over speculative futures.

AI Ecosystems, Infrastructure and Security

Ward-Foxton often writes about the broader ecosystems around AI hardware, including infrastructure, reliability, and security. In pieces such as “Physical AI Needs An Ecosystem,” she describes how advances in AI, safety, and silicon ecosystems are enabling smarter, safer robots that work alongside humans, framing hardware innovation within system-level requirements.

Her newsletter and podcast work digs into the networking challenges of large-scale AI training, including discussions of training courses that scale to hundreds of thousands of GPUs and the pressure that puts on interconnect reliability and system design. She hosts EE Times’ AI-focused podcast, where episodes like “Can Disaggregated Memory Reshape AI Inference?” explore how memory architectures for inference workloads might need to change to keep pace with model growth. In another podcast appearance, she discusses how AI is lowering the barriers to finding security vulnerabilities and why hardware could become the next frontier for security, tying software-driven threat discovery to potential shifts in chip and system design.

This strand of her work makes clear that she views AI silicon in the context of networks, tools, and security practices that determine whether chips perform as advertised in real deployments.

Interviews, Podcasts and Industry Leadership

Interviews with executives and technologists are central to Ward-Foxton’s reporting style, and she frequently uses long-form conversations to surface practical detail on AI and semiconductor strategy. She has compiled an interview series with top semiconductor CEOs, focusing on lessons learned and perspectives on where the industry is headed, and brings these voices into EE Times’ coverage of AI and chips. At the Embedded Vision Summit, she appears as an interviewer and moderator, including a session titled “Beyond TOPS - Evaluating and Selecting Processors for Edge AI and Vision,” where she talks with RetailNext’s director of technology about how to evaluate processors for edge AI and vision workloads beyond simple performance metrics.

Her summit speaker role also reflects her remit: she covers AI technology and related issues for EE Times and all aspects of the European semiconductor industry for its European magazine, giving her a cross-cutting view of regional and global trends.

In addition to written work, she hosts EE Times’ “AI with Sally” podcast, introducing episodes and guiding discussions that blend technical depth with business and ecosystem insight. Taken together, these interviews, podcasts, and event sessions show a reporter who is deeply embedded in the AI hardware community and who uses direct conversations with practitioners to inform her coverage of accelerators, edge devices, and the markets around them.